303 resultados para image reduction algorith


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Canine distemper virus (CDV), a mobillivirus related to measles virus causes a chronic progressive demyelinating disease, associated with persistence of the virus in the central nervous system (CNS). CNS persistence of morbilliviruses has been associated with cell-to-cell spread, thereby limiting immune detection. The mechanism of cell-to-cell spread remains uncertain. In the present study we studied viral spread comparing a cytolytic (non-persistent) and a persistent CDV strain in cell cultures. Cytolytic CDV spread in a compact concentric manner with extensive cell fusion and destruction of the monolayer. Persistent CDV exhibited a heterogeneous cell-to-cell pattern of spread without cell fusion and 100-fold reduction of infectious viral titers in supernatants as compared to the cytolytic strain. Ultrastructurally, low infectious titers correlated with limited budding of persistent CDV as compared to the cytolytic strain, which shed large numbers of viral particles. The pattern of heterogeneous cell-to-cell viral spread can be explained by low production of infectious viral particles in only few areas of the cell membrane. In this way persistent CDV only spreads to a small proportion of the cells surrounding an infected one. Our studies suggest that both cell-to-cell spread and limited production of infectious virus are related to reduced expression of fusogenic complexes in the cell membrane. Such complexes consist of a synergistic configuration of the attachment (H) and fusion (F) proteins on the cell surface. F und H proteins exhibited a marked degree of colocalization in cytolytic CDV infection but not in persistent CDV as seen by confocal laser microscopy. In addition, analysis of CDV F protein expression using vaccinia constructs of both strains revealed an additional large fraction of uncleaved fusion protein in the persistent strain. This suggests that the paucity of active fusion complexes is due to restricted intracellular processing of the viral fusion protein.

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BACKGROUND & AIMS: Despite the proven ability of immunization to reduce Helicobacter infection in mouse models, the precise mechanism of protection has remained elusive. This study explores the possibility that interleukin (IL)-17 plays a role in the reduction of Helicobacter infection following vaccination of wild-type animals or in spontaneous reduction of bacterial infection in IL-10-deficient mice. METHODS: In mice, reducing Helicobacter infection, the levels and source of IL-17 were determined and the role of IL-17 in reduction of Helicobacter infection was probed by neutralizing antibodies. RESULTS: Gastric IL-17 levels were strongly increased in mice mucosally immunized with urease plus cholera toxin and challenged with Helicobacter felis as compared with controls (654 +/- 455 and 34 +/- 84 relative units for IL-17 messenger RNA expression [P < .01] and 6.9 +/- 8.4 and 0.02 +/- 0.04 pg for IL-17 protein concentration [P < .01], respectively). Flow cytometry analysis showed that a peak of CD4(+)IL-17(+) T cells infiltrating the gastric mucosa occurred in immunized mice in contrast to control mice (4.7% +/- 0.3% and 1.4% +/- 0.3% [P < .01], respectively). Gastric mucosa-infiltrating CD4(+)IL-17(+) T cells were also observed in IL-10-deficient mice that spontaneously reduced H felis infection (4.3% +/- 2.3% and 2% +/- 0.6% [P < .01], for infected and noninfected IL-10-deficient mice, respectively). In wild-type immunized mice, intraperitoneal injection of anti-IL-17 antibodies significantly inhibited inflammation and the reduction of Helicobacter infection in comparison with control antibodies (1 of 12 mice vs 9 of 12 mice reduced Helicobacter infection [P < .01], respectively). CONCLUSIONS: IL-17 plays a critical role in the immunization-induced reduction of Helicobacter infection from the gastric mucosa.

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The goal of this work is to develop a method to objectively compare the performance of a digital and a screen-film mammography system in terms of image quality. The method takes into account the dynamic range of the image detector, the detection of high and low contrast structures, the visualisation of the images and the observer response. A test object, designed to represent a compressed breast, was constructed from various tissue equivalent materials ranging from purely adipose to purely glandular composition. Different areas within the test object permitted the evaluation of low and high contrast detection, spatial resolution and image noise. All the images (digital and conventional) were captured using a CCD camera to include the visualisation process in the image quality assessment. A mathematical model observer (non-prewhitening matched filter), that calculates the detectability of high and low contrast structures using spatial resolution, noise and contrast, was used to compare the two technologies. Our results show that for a given patient dose, the detection of high and low contrast structures is significantly better for the digital system than for the conventional screen-film system studied. The method of using a test object with a large tissue composition range combined with a camera to compare conventional and digital imaging modalities can be applied to other radiological imaging techniques. In particular it could be used to optimise the process of radiographic reading of soft copy images.

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We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

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During conventional x-ray coronary angiography, multiple projections of the coronary arteries are acquired to define coronary anatomy precisely. Due to time constraints, coronary magnetic resonance angiography (MRA) usually provides only one or two views of the major coronary vessels. A coronary MRA approach that allowed for reconstruction of arbitrary isotropic orientations might therefore be desirable. The purpose of the study was to develop a three-dimensional (3D) coronary MRA technique with isotropic image resolution in a relatively short scanning time that allows for reconstruction of arbitrary views of the coronary arteries without constraints given by anisotropic voxel size. Eight healthy adult subjects were examined using a real-time navigator-gated and corrected free-breathing interleaved echoplanar (TFE-EPI) 3D-MRA sequence. Two 3D datasets were acquired for the left and right coronary systems in each subject, one with anisotropic (1.0 x 1.5 x 3.0 mm, 10 slices) and one with "near" isotropic (1.0 x 1.5 x 1.0 mm, 30 slices) image resolution. All other imaging parameters were maintained. In all cases, the entire left main (LM) and extensive portions of the left anterior descending (LAD) and the right coronary artery (RCA) were visualized. Objective assessment of coronary vessel sharpness was similar (41% +/- 5% vs. 42% +/- 5%; P = NS) between in-plane and through-plane views with "isotropic" voxel size but differed (32% +/- 7% vs. 23% +/- 4%; P < 0.001) with nonisotropic voxel size. In reconstructed views oriented in the through-plane direction, the vessel border was 86% more defined (P < 0.01) for isotropic compared with anisotropic images. A smaller (30%; P < 0.001) improvement was seen for in-plane reconstructions. Vessel diameter measurements were view independent (2.81 +/- 0.45 mm vs. 2.66 +/- 0.52 mm; P = NS) for isotropic, but differed (2.71 +/- 0.51 mm vs. 3.30 +/- 0.38 mm; P < 0.001) between anisotropic views. Average scanning time was 2:31 +/- 0:57 minutes for anisotropic and 7:11 +/- 3:02 minutes for isotropic image resolution (P < 0.001). We present a new approach for "near" isotropic 3D coronary artery imaging, which allows for reconstruction of arbitrary views of the coronary arteries. The good delineation of the coronary arteries in all views suggests that isotropic 3D coronary MRA might be a preferred technique for the assessment of coronary disease, although at the expense of prolonged scan times. Comparative studies with conventional x-ray angiography are needed to investigate the clinical utility of the isotropic strategy.

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INTRODUCTION: Adaptive statistical iterative reconstruction (ASIR) can decrease image noise, thereby generating CT images of comparable diagnostic quality with less radiation. The purpose of this study is to quantify the effect of systematic use of ASIR versus filtered back projection (FBP) for neuroradiology CT protocols on patients' radiation dose and image quality. METHODS: We evaluated the effect of ASIR on six types of neuroradiologic CT studies: adult and pediatric unenhanced head CT, adult cervical spine CT, adult cervical and intracranial CT angiography, adult soft tissue neck CT with contrast, and adult lumbar spine CT. For each type of CT study, two groups of 100 consecutive studies were retrospectively reviewed: 100 studies performed with FBP and 100 studies performed with ASIR/FBP blending factor of 40 %/60 % with appropriate noise indices. The weighted volume CT dose index (CTDIvol), dose-length product (DLP) and noise were recorded. Each study was also reviewed for image quality by two reviewers. Continuous and categorical variables were compared by t test and free permutation test, respectively. RESULTS: For adult unenhanced brain CT, CT cervical myelography, cervical and intracranial CT angiography and lumbar spine CT both CTDIvol and DLP were lowered by up to 10.9 % (p < 0.001), 17.9 % (p = 0.005), 20.9 % (p < 0.001), and 21.7 % (p = 0.001), respectively, by using ASIR compared with FBP alone. Image quality and noise were similar for both FBP and ASIR. CONCLUSION: We recommend routine use of iterative reconstruction for neuroradiology CT examinations because this approach affords a significant dose reduction while preserving image quality.

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In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

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Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.

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